{
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  {
   "cell_type": "markdown",
   "id": "b0541e6a",
   "metadata": {},
   "source": [
    "# roberta-large-ner-english: model fine-tuned from roberta-large for NER task\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c85540d7",
   "metadata": {},
   "source": [
    "## Introduction\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c2e2ebde",
   "metadata": {},
   "source": [
    "roberta-large-ner-english is an english NER model that was fine-tuned from roberta-large on conll2003 dataset.\n",
    "Model was validated on emails/chat data and outperformed other models on this type of data specifically.\n",
    "In particular the model seems to work better on entity that don't start with an upper case.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4f6d5dbe",
   "metadata": {},
   "source": [
    "## How to use"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a159cf92",
   "metadata": {},
   "outputs": [],
   "source": [
    "!pip install --upgrade paddlenlp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "daa60299",
   "metadata": {},
   "outputs": [],
   "source": [
    "import paddle\n",
    "from paddlenlp.transformers import AutoModel\n",
    "\n",
    "model = AutoModel.from_pretrained(\"Jean-Baptiste/roberta-large-ner-english\")\n",
    "input_ids = paddle.randint(100, 200, shape=[1, 20])\n",
    "print(model(input_ids))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2a66154e",
   "metadata": {},
   "source": [
    "For those who could be interested, here is a short article on how I used the results of this model to train a LSTM model for signature detection in emails:\n",
    "https://medium.com/@jean-baptiste.polle/lstm-model-for-email-signature-detection-8e990384fefa\n",
    "\n",
    "> The model introduction and model weights originate from  https://huggingface.co/Jean-Baptiste/roberta-large-ner-english  and were converted to PaddlePaddle format for ease of use in PaddleNLP."
   ]
  }
 ],
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